Wan Tang

3.4k citations
89 papers · 2.3k indexed · h-index 25

Wan Tang

84 papers receiving 2.2k citations

Peers

Wan Tang
Comparison fields: 5 of 178
  • Neuropsychology and Physiological Psychology 57
  • Health 294
  • Statistics and Probability 195
  • Clinical Psychology 455
  • Obstetrics and Gynecology 147
Replace Mark Oremus with:
Mark Oremus Canada
Haroutune K. Armenian United States
Juned Siddique United States
Hisashi Noma Japan
Bruce Levin United States
Afisi Ismaila Canada
Hua He United States
Morten Frydenberg Denmark
John W. Jackson United States
Richard Kennedy United States
Wan Tang relative to Mark Oremus Canada Mark Oremus's profile →
Citations per field
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Citations per year

Countries citing papers authored by Wan Tang

Since Specialization
Citations

This map shows the geographic impact of Wan Tang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Wan Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wan Tang more than expected).

Fields of papers citing papers by Wan Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wan Tang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Wan Tang. The network helps show where Wan Tang may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Wan Tang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Wan Tang Line = papers co-authored together Wan Tang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 20242
3 20233
4 202313
5 20222
6 202210
7 20210
8 20169
9
The optimization scheme of Mongolian gerbils superovulation induced by PMSG and hCG
20151
10 201412
11
Long-term indwelling urinary catheter problems
20121
12 201124
13 20117
14 201123
15 201035
16 201018
17 200824
18 200813
19 20078
20 2006101

About Wan Tang

Wan Tang is a scholar working on Statistics and Probability, Neuropsychology and Physiological Psychology, Urology, Health and Statistics, Probability and Uncertainty, having authored 89 papers that have together received 2.3k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (18 papers), Statistical Methods and Inference (14 papers), Advanced Causal Inference Techniques (9 papers), Statistical Methods in Clinical Trials (7 papers), Urinary Tract Infections Management (6 papers), Urinary Bladder and Prostate Research (6 papers), Pelvic floor disorders treatments (5 papers) and Bayesian Methods and Mixture Models (5 papers). The work is most often cited by research in Neuropsychology and Physiological Psychology (57 citations), Health (294 citations), Statistics and Probability (195 citations), Clinical Psychology (455 citations) and Obstetrics and Gynecology (147 citations). Wan Tang has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Xin Tu, Hua He, Thomas G. O’Connor, Emma Robertson Blackmore, Nancy L. Talbot, Yeates Conwell, Jeffrey M. Lyness, Changyong Feng, Linda H. Chaudron and Catherine Cerulli. Their work appears in journals such as Statistical Methods in Medical Research, Statistics in Medicine, Journal of Statistical Planning and Inference, American Journal of Geriatric Psychiatry and Nursing Research.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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